Guillermo Martinez-Boggio , Patrick Lutz , Meredith Harrison , Kent A. Weigel , Francisco Peñagaricano
{"title":"greenfeedr:一个R包,用于处理和报告GreenFeed数据","authors":"Guillermo Martinez-Boggio , Patrick Lutz , Meredith Harrison , Kent A. Weigel , Francisco Peñagaricano","doi":"10.3168/jdsc.2024-0662","DOIUrl":null,"url":null,"abstract":"<div><div>Greenhouse gases produced by livestock are important contributors to climate change. The ability to measure large-scale exhaled metabolic gases from cattle using GreenFeed systems will help farmers to reduce enteric emissions while maintaining or increasing cow productivity. GreenFeed units are portable chamber systems that measure individual animal gas production in real time. Thus, the machines generate large amounts of daily data that can be overwhelming for users to process. This challenge motivated us to develop an R package named <em>greenfeedr</em> that offers functions for downloading, processing, and reporting GreenFeed data. Herein, we describe all functions implemented in the <em>greenfeedr</em> R package and present examples based on dairy cow data. The R package has functions for downloading GreenFeed data (<em>get_gfdata</em>), for generating daily and final reports (<em>report_gfdata</em>), for processing daily and final records (<em>process_gfdata</em>), and extra functions that help to extract information regarding pellet intakes and daily visits (<em>pellin</em> and <em>viseat</em>). Using our example data with 32 lactating dairy cows, we demonstrated the capabilities of the different functions to generate easy-to-read reports and process large amount of data. Also, we included in the function <em>process_gfdata</em> some parameters that will help users to define the best criteria to process their own GreenFeed data. Overall, <em>greenfeedr</em> represents an important advancement in the management and analysis of GreenFeed data, offering an efficient tool tailored to the needs of the user.</div></div>","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"6 2","pages":"Pages 227-230"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"greenfeedr: An R package for processing and reporting GreenFeed data\",\"authors\":\"Guillermo Martinez-Boggio , Patrick Lutz , Meredith Harrison , Kent A. Weigel , Francisco Peñagaricano\",\"doi\":\"10.3168/jdsc.2024-0662\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Greenhouse gases produced by livestock are important contributors to climate change. The ability to measure large-scale exhaled metabolic gases from cattle using GreenFeed systems will help farmers to reduce enteric emissions while maintaining or increasing cow productivity. GreenFeed units are portable chamber systems that measure individual animal gas production in real time. Thus, the machines generate large amounts of daily data that can be overwhelming for users to process. This challenge motivated us to develop an R package named <em>greenfeedr</em> that offers functions for downloading, processing, and reporting GreenFeed data. Herein, we describe all functions implemented in the <em>greenfeedr</em> R package and present examples based on dairy cow data. The R package has functions for downloading GreenFeed data (<em>get_gfdata</em>), for generating daily and final reports (<em>report_gfdata</em>), for processing daily and final records (<em>process_gfdata</em>), and extra functions that help to extract information regarding pellet intakes and daily visits (<em>pellin</em> and <em>viseat</em>). Using our example data with 32 lactating dairy cows, we demonstrated the capabilities of the different functions to generate easy-to-read reports and process large amount of data. Also, we included in the function <em>process_gfdata</em> some parameters that will help users to define the best criteria to process their own GreenFeed data. Overall, <em>greenfeedr</em> represents an important advancement in the management and analysis of GreenFeed data, offering an efficient tool tailored to the needs of the user.</div></div>\",\"PeriodicalId\":94061,\"journal\":{\"name\":\"JDS communications\",\"volume\":\"6 2\",\"pages\":\"Pages 227-230\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JDS communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S266691022400187X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JDS communications","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266691022400187X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
greenfeedr: An R package for processing and reporting GreenFeed data
Greenhouse gases produced by livestock are important contributors to climate change. The ability to measure large-scale exhaled metabolic gases from cattle using GreenFeed systems will help farmers to reduce enteric emissions while maintaining or increasing cow productivity. GreenFeed units are portable chamber systems that measure individual animal gas production in real time. Thus, the machines generate large amounts of daily data that can be overwhelming for users to process. This challenge motivated us to develop an R package named greenfeedr that offers functions for downloading, processing, and reporting GreenFeed data. Herein, we describe all functions implemented in the greenfeedr R package and present examples based on dairy cow data. The R package has functions for downloading GreenFeed data (get_gfdata), for generating daily and final reports (report_gfdata), for processing daily and final records (process_gfdata), and extra functions that help to extract information regarding pellet intakes and daily visits (pellin and viseat). Using our example data with 32 lactating dairy cows, we demonstrated the capabilities of the different functions to generate easy-to-read reports and process large amount of data. Also, we included in the function process_gfdata some parameters that will help users to define the best criteria to process their own GreenFeed data. Overall, greenfeedr represents an important advancement in the management and analysis of GreenFeed data, offering an efficient tool tailored to the needs of the user.